Reinforcement Learning for Electricity Network Operation
It facilitates collaboration between the machine learning and power systems communities for a domain-specific challenge.
The paper introduces background material for a challenge that uses reinforcement learning to manage real-time power grid operations, aiming to balance power flows and maintain stability.
This paper presents the background material required for the Learning to Run Power Networks Challenge. The challenge is focused on using Reinforcement Learning to train an agent to manage the real-time operations of a power grid, balancing power flows and making interventions to maintain stability. We present an introduction to power systems targeted at the machine learning community and an introduction to reinforcement learning targeted at the power systems community. This is to enable and encourage broader participation in the challenge and collaboration between these two communities.